Live opening · Posted 3 days ago

Lead Analyst, Payment Abuse Operations'

LinkedIn · Bengaluru, Karnataka, India (Hybrid)
Linkedin Hybrid
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At a glance

The key details from the original listing.

Posted 3 days ago
CompanyLinkedIn
LocationBengaluru, Karnataka, India (Hybrid)
Work modeHybrid
SourceLinkedin
ListedPosted 3 days ago

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About the role

Description supplied by the original job listing.

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun – where everyone can succeed.
Join us to transform the way the world works.
Job Description
Team Overview
LinkedIn's Trust Operations team is maturing its Payment Abuse function, and we're looking for a Lead Analyst to help take it to the next level. You will lead complex investigations, raise the standard for how we detect and remediate payment fraud, and turn ad hoc practices into scalable controls, workflows, and monitoring. This is a senior individual contributor role with no direct reports, on a global team, with significant cross-functional influence and ownership of outcomes.
The ideal candidate combines deep payments-risk expertise, strong analytical capabilities, and operational leadership to navigate complex business challenges. This individual will lead investigations and strategic initiatives, identify emerging risks and control gaps, influence stakeholders, and serve as a subject matter expert within the Payment Abuse organization.
At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
Key Responsibilities
Lead complex payment fraud and abuse investigations end to end: find root causes and control gaps, and drive remediation to closure.
Monitor fraud and chargeback performance against payment network and regulatory threshold, investigate the drivers, and lead remediation when performance trends toward a threshold.
Use SQL and data analysis to surface emerging fraud trends, define risk metrics and KPIs, and turn findings into operational and product improvements.
Design and strengthen fraud controls, monitoring frameworks, and tooling, including finding opportunities for automation and ML-assisted detection.
Strengthen operational rigor by standardizing and documenting SOPs, investigation playbooks, and escalation criteria across the team.
Partner with our vendor partner on payments workflows by setting escalation criteria, defining quality signals, and making sure SOPs are applied consistently.
Partner with Product, Engineering, Data Science, Payments, Operations, and external payment partners to resolve complex payment-risk challenges.
Serve as the escalation point for high-risk cases, and mentor analysts as the team's subject matter expert.
Own initiatives from problem identification through implementation and impact measurement, communicating effectively and operating effectively in ambiguous environments.
Contribute to operational strategy, regional coverage planning, and the long-term Payment Abuse roadmap.
Qualifications
Basic Qualifications
5+ years of experience in payment fraud, payment abuse, payments risk, or a related field, including experience leading complex fraud, chargeback, or dispute investigations.
3+ years of experience with payment processors, acquirers, card-network rules, fraud-monitoring programs, chargeback programs, or scheme-compliance and remediation initiatives (VAMP, Mastercard, Auspaynet).
3+ years of experience designing or enhancing fraud controls, monitoring frameworks, and risk mitigation strategies supporting payment abuse prevention, chargeback management, or scheme-compliance programs.
3+ years of hands-on SQL and data-analysis experience, including analyzing large datasets, identifying fraud trends, defining risk metrics or KPIs, and translating findings into operational or product improvements.
Preferred Qualifications
Experience operating in a global, high-volume digital payments environment.
Experience with alternative payment methods and regional ecosystems, such as SEPA, iDEAL, ACH, and digital wallets.
Track record of influencing product, policy, or platform changes to reduce abuse risk.
Experience maturing an existing function by formalizing processes, raising quality standards, or evolving its operating model.
Experience overseeing work delivered by vendors or managed service providers.
Experience mentoring analysts in a payments risk, fraud, or Trust & Safety organization.
Suggested Skills
Payment & Fraud Abuse • Payments Risk • Scheme Compliance & Risk Management • Chargebacks & Disputes • Fraud Investigation • Root-Cause Analysis • SQL & Data Analysis • Control Design • Risk Monitoring & Remediation • Process Optimization • Vendor Oversight • Cross-Functional Leadership • Stakeholder Influence • Mentorship
Additional Information
India Disability Policy
LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf
Global Data Privacy Notice and Compliance Posters for Job Candidates
Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal.

Work arrangement
Hybrid

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